Andrew Zhang

1.7k total citations · 2 hit papers
6 papers, 619 citations indexed

About

Andrew Zhang is a scholar working on Artificial Intelligence, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Andrew Zhang has authored 6 papers receiving a total of 619 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 2 papers in Molecular Biology and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Andrew Zhang's work include AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Biomedical Text Mining and Ontologies (2 papers). Andrew Zhang is often cited by papers focused on AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Biomedical Text Mining and Ontologies (2 papers). Andrew Zhang collaborates with scholars based in United States, Philippines and Canada. Andrew Zhang's co-authors include Bowen Chen, Guillaume Jaume, Faisal Mahmood, Drew F. K. Williamson, Richard J. Chen, Long P. Le, Georg K. Gerber, Ming Y. Lu, Tong Ding and Anil V. Parwani and has published in prestigious journals such as Cell, Nature Medicine and Neuro-Oncology.

In The Last Decade

Andrew Zhang

4 papers receiving 605 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Towards a general-purpose foundation model for computational pathology

2024 331 citations Richard J. Chen, Tong Ding et al. Nature Medicine profile →
A visual-language foundation model for computational pathology

2024 228 citations Ming Y. Lu, Bowen Chen et al. Nature Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Andrew Zhang United States	4	362	265	120	88	84	6	619
Maha Shady United States	5	354 1.0×	270 1.0×	91 0.8×	97 1.1×	70 0.8×	10	522
Luca L. Weishaupt United States	3	288 0.8×	225 0.8×	85 0.7×	65 0.7×	61 0.7×	6	499
Mane Williams United States	5	431 1.2×	338 1.3×	110 0.9×	127 1.4×	107 1.3×	6	707
Nikolas Stathonikos Netherlands	14	508 1.4×	328 1.2×	163 1.4×	78 0.9×	124 1.5×	32	687
Jerome Cheng United States	14	305 0.8×	185 0.7×	75 0.6×	117 1.3×	101 1.2×	49	627
Chengkuan Chen United States	4	488 1.3×	372 1.4×	177 1.5×	113 1.3×	81 1.0×	5	807
Sharifa Sahai United States	2	299 0.8×	213 0.8×	76 0.6×	62 0.7×	64 0.8×	3	585
Giovanni Lujan United States	11	325 0.9×	217 0.8×	65 0.5×	74 0.8×	111 1.3×	20	584
Żaneta Świderska-Chadaj Poland	13	360 1.0×	273 1.0×	141 1.2×	64 0.7×	103 1.2×	30	582
Pooya Mobadersany United States	5	432 1.2×	420 1.6×	94 0.8×	114 1.3×	105 1.3×	9	716

Countries citing papers authored by Andrew Zhang

Since Specialization

Citations

This map shows the geographic impact of Andrew Zhang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andrew Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Zhang more than expected).

Fields of papers citing papers by Andrew Zhang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew Zhang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andrew Zhang. The network helps show where Andrew Zhang may publish in the future.

Co-authorship network of co-authors of Andrew Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Zhang. A scholar is included among the top collaborators of Andrew Zhang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andrew Zhang. Andrew Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

6 of 6 papers shown

1.

Zhang, Andrew, et al.. (2025). Maximal Matching Matters: Preventing Representation Collapse for Robust Cross-Modal Retrieval. 31769–31785.

2.

Song, Andrew H., Mane Williams, Drew F. K. Williamson, et al.. (2024). Analysis of 3D pathology samples using weakly supervised AI. Cell. 187(10). 2502–2520.e17. 27 indexed citations

3.

Lu, Ming Y., Bowen Chen, Drew F. K. Williamson, et al.. (2024). A visual-language foundation model for computational pathology. Nature Medicine. 30(3). 863–874. 228 indexed citations breakdown →

4.

Chen, Richard J., Tong Ding, Ming Y. Lu, et al.. (2024). Towards a general-purpose foundation model for computational pathology. Nature Medicine. 30(3). 850–862. 331 indexed citations breakdown →

5.

Ayoub, Georges, Seth Malinowski, Anurag Vaidya, et al.. (2024). PATH-50. AI-POWERED AUTOMATED TISSUE SEGMENTATION IMPROVES OUTCOME STRATIFICATION IN GLIOBLASTOMA. Neuro-Oncology. 26(Supplement_8). viii190–viii190.

6.

Alberto, Nicole Rose I., Arnab K. Ghosh, Bhav Jain, et al.. (2023). The impact of commercial health datasets on medical research and health-care algorithms. The Lancet Digital Health. 5(5). e288–e294. 33 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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